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Combined Optimal Sizing and Control for a Hybrid Tracked Vehicle

Author

Listed:
  • Yuan Zou

    (National Engineering Lab for Electric Vehicles, School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China)

  • Fengchun Sun

    (National Engineering Lab for Electric Vehicles, School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China)

  • Xiaosong Hu

    (National Engineering Lab for Electric Vehicles, School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China)

  • Lino Guzzella

    (Institute of Dynamic Systems and Control, Department of Mechanical and Process Engineering, Swiss Federal Institute of Technology, Zurich 8001, Switzerland)

  • Huei Peng

    (Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109, USA)

Abstract

The optimal sizing and control of a hybrid tracked vehicle is presented and solved in this paper. A driving schedule obtained from field tests is used to represent typical tracked vehicle operations. Dynamics of the diesel engine-permanent magnetic AC synchronous generator set, the lithium-ion battery pack, and the power split between them are modeled and validated through experiments. Two coupled optimizations, one for the plant parameters, forming the outer optimization loop and one for the control strategy, forming the inner optimization loop, are used to achieve minimum fuel consumption under the selected driving schedule. The dynamic programming technique is applied to find the optimal controller in the inner loop while the component parameters are optimized iteratively in the outer loop. The results are analyzed, and the relationship between the key parameters is observed to keep the optimal sizing and control simultaneously.

Suggested Citation

  • Yuan Zou & Fengchun Sun & Xiaosong Hu & Lino Guzzella & Huei Peng, 2012. "Combined Optimal Sizing and Control for a Hybrid Tracked Vehicle," Energies, MDPI, vol. 5(11), pages 1-14, November.
    • Handle: RePEc:gam:jeners:v:5:y:2012:i:11:p:4697-4710:d:21543
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    Citations

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    Cited by:

    1. Du, Guodong & Zou, Yuan & Zhang, Xudong & Liu, Teng & Wu, Jinlong & He, Dingbo, 2020. "Deep reinforcement learning based energy management for a hybrid electric vehicle," Energy, Elsevier, vol. 201(C).
    2. Zhenpo Wang & Changhui Qu & Lei Zhang & Jin Zhang & Wen Yu, 2018. "Integrated Sizing and Energy Management for Four-Wheel-Independently-Actuated Electric Vehicles Considering Realistic Constructed Driving Cycles," Energies, MDPI, vol. 11(7), pages 1-22, July.
    3. Ernest Cortez & Manuel Moreno-Eguilaz & Francisco Soriano, 2018. "Advanced Methodology for the Optimal Sizing of the Energy Storage System in a Hybrid Electric Refuse Collector Vehicle Using Real Routes," Energies, MDPI, vol. 11(12), pages 1-17, November.
    4. Ouyang, Minggao & Feng, Xuning & Han, Xuebing & Lu, Languang & Li, Zhe & He, Xiangming, 2016. "A dynamic capacity degradation model and its applications considering varying load for a large format Li-ion battery," Applied Energy, Elsevier, vol. 165(C), pages 48-59.
    5. Du, Guodong & Zou, Yuan & Zhang, Xudong & Guo, Lingxiong & Guo, Ningyuan, 2022. "Energy management for a hybrid electric vehicle based on prioritized deep reinforcement learning framework," Energy, Elsevier, vol. 241(C).
    6. Pinto, Cláudio & Barreras, Jorge V. & de Castro, Ricardo & Araújo, Rui Esteves & Schaltz, Erik, 2017. "Study on the combined influence of battery models and sizing strategy for hybrid and battery-based electric vehicles," Energy, Elsevier, vol. 137(C), pages 272-284.
    7. Huang, Yanjun & Wang, Hong & Khajepour, Amir & Li, Bin & Ji, Jie & Zhao, Kegang & Hu, Chuan, 2018. "A review of power management strategies and component sizing methods for hybrid vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 132-144.
    8. Jianjun Hu & Lingling Zheng & Meixia Jia & Yi Zhang & Tao Pang, 2018. "Optimization and Model Validation of Operation Control Strategies for a Novel Dual-Motor Coupling-Propulsion Pure Electric Vehicle," Energies, MDPI, vol. 11(4), pages 1-14, March.
    9. Guyadec, M. Le & Gerbaud, L. & Vinot, E. & Reinbold, V. & Dumont, C., 2019. "Use of reluctance network modelling and software component to study the influence of electrical machine pole number on hybrid electric vehicle global optimization," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 158(C), pages 79-90.
    10. Zou, Yuan & Liu, Teng & Liu, Dexing & Sun, Fengchun, 2016. "Reinforcement learning-based real-time energy management for a hybrid tracked vehicle," Applied Energy, Elsevier, vol. 171(C), pages 372-382.
    11. Yalian Yang & Xiaosong Hu & Datong Qing & Fangyuan Chen, 2013. "Arrhenius Equation-Based Cell-Health Assessment: Application to Thermal Energy Management Design of a HEV NiMH Battery Pack," Energies, MDPI, vol. 6(5), pages 1-17, May.
    12. Yu-Huei Cheng & Ching-Ming Lai, 2017. "Control Strategy Optimization for Parallel Hybrid Electric Vehicles Using a Memetic Algorithm," Energies, MDPI, vol. 10(3), pages 1-21, March.
    13. Du, Guodong & Zou, Yuan & Zhang, Xudong & Kong, Zehui & Wu, Jinlong & He, Dingbo, 2019. "Intelligent energy management for hybrid electric tracked vehicles using online reinforcement learning," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    14. Teng Liu & Yuan Zou & Dexing Liu & Fengchun Sun, 2015. "Reinforcement Learning–Based Energy Management Strategy for a Hybrid Electric Tracked Vehicle," Energies, MDPI, vol. 8(7), pages 1-18, July.
    15. Xue, Nansi & Du, Wenbo & Greszler, Thomas A. & Shyy, Wei & Martins, Joaquim R.R.A., 2014. "Design of a lithium-ion battery pack for PHEV using a hybrid optimization method," Applied Energy, Elsevier, vol. 115(C), pages 591-602.
    16. Wei, Shouyang & Zou, Yuan & Sun, Fengchun & Christopher, Onder, 2017. "A pseudospectral method for solving optimal control problem of a hybrid tracked vehicle," Applied Energy, Elsevier, vol. 194(C), pages 588-595.
    17. Tobias Nüesch & Philipp Elbert & Michael Flankl & Christopher Onder & Lino Guzzella, 2014. "Convex Optimization for the Energy Management of Hybrid Electric Vehicles Considering Engine Start and Gearshift Costs," Energies, MDPI, vol. 7(2), pages 1-23, February.
    18. Nissim Amar & Aaron Shmaryahu & Michael Coletti & Ilan Aharon, 2021. "Sizing Procedure for System Hybridization Based on Experimental Source Modeling in Grid Application," Energies, MDPI, vol. 14(15), pages 1-19, August.

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